19 citations · 30 across the 7 of their papers we have counts for
5 papers
SyllableLM: Learning Coarse Semantic Units for Speech Language Models
Alan Baade, Puyuan Peng, David Harwath
Language models require tokenized inputs. However, tokenization strategies for continuous data like audio and vision are often based on simple heuristics such as fixed sized convol…
Zero-shot Video Moment Retrieval With Off-the-Shelf Models
Anuj Diwan, Puyuan Peng, Raymond J. Mooney
For the majority of the machine learning community, the expensive nature of collecting high-quality human-annotated data and the inability to efficiently finetune very large state-…
MAE-AST: Masked Autoencoding Audio Spectrogram Transformer
Alan Baade, Puyuan Peng, David Harwath
In this paper, we propose a simple yet powerful improvement over the recent Self-Supervised Audio Spectrogram Transformer (SSAST) model for speech and audio classification. Specifi…
Self-Supervised Representation Learning for Speech Using Visual Grounding and Masked Language Modeling
Puyuan Peng, David Harwath
In this paper, we describe our submissions to the ZeroSpeech 2021 Challenge and SUPERB benchmark. Our submissions are based on the recently proposed FaST-VGS model, which is a Tran…
A Correspondence Variational Autoencoder for Unsupervised Acoustic Word Embeddings
Puyuan Peng, Herman Kamper, Karen Livescu
We propose a new unsupervised model for mapping a variable-duration speech segment to a fixed-dimensional representation. The resulting acoustic word embeddings can form the basis…